This post (and my presentation) explores the concept of the ‘smart’ city and lays the groundwork for a discussion of governance by exploring the different types of data collected in so-called smart cities.

Although the term ‘smart city’ is often bandied about, there is no common understanding of what it means. Anthony Townsend has defined smart cities as “places where information technology is combined with infrastructure, architecture, everyday objects, and even our bodies to address social, economic, and environmental problems.” (A. Townsend, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. (New York: W.W. Norton & Co., 2013), at p. 15). This definition emphasizes the embedding of information technologies within cities with the goal of solving a broad range of urban problems. Still, there is uncertainty as to which cities are ‘smart’ or at what point a city passes the invisible ‘smart’ threshold.

Embedded technologies are multiple and ever-evolving, and many are already in place in the cities in which we live. Technologies that have become relatively commonplace include smart transit cards, GPS systems on public vehicles (e.g.: buses, snowplows, emergency vehicles, etc.), smart metering for utilities, and surveillance and traffic cameras. Many of the technologies just identified collect data; smart technologies also process data using complex algorithms to generate analytics that can be used in problem identification and problem solving. Predictive policing is an example of a technology that generates information based on input data and complex algorithms.

While it is possible for a smart city to be built from the ground up, this is not the most common type of smart city. Instead, most cities become ‘smarter’ by increments, as governments adopt one technology after another to address particular needs and issues. While both from-the-ground-up and incremental smart cities raise important governance issues, it is the from-the-ground-up projects (such as Sidewalk Toronto) that get the most public attention. With incremental smart cities, the piecemeal adoption of technologies often occurs quietly, without notice, and thus potentially without proper attention being paid to important overarching governance issues such as data ownership and control, privacy, transparency, and security.

Canada has seen two major smart cities initiatives launched in the last year. These are the federal government’s Smart Cities Challenge – a contest between municipalities to fund the development of smart cities projects – and the Sidewalk Toronto initiative to create a from-the-ground-up smart development in Toronto’s Quayside area. Although Canadian cities have been becoming ‘smart’ by increments for some time now, these two high-profile initiatives have sparked discussion of the public policy issues, bringing important governance issues to the forefront.

These initiatives, like many others, have largely been conceived of and presented to the public as technology, infrastructure, and economic development projects. Rather than acknowledging up-front the need for governance innovation to accompany the emerging technologies, governance tends to get lost in the hype. Yet it is crucial. Smart cities feed off data, and residents are primary sources. Much of the data collected in smart cities is personal information, raising obvious privacy issues. Issues of ownership and control over smart cities data (whether personal or non-personal) are also important. They are relevant to who gets to access and use the data, for what purposes, and for whose profit. The public outcry over the Sidewalk Toronto project (examples here, here and here) clearly demonstrates that cities are not just tech laboratories; they are the places where we try to live decent and meaningful lives.

The governance issues facing so-called smart cities are complex. They may be difficult to disentangle from the prevailing ‘innovate or perish’ discourse. They are also rooted in technologies that are rapidly evolving. Existing laws and legal and policy frameworks may not be fully adequate to address smart cities challenges. This means that the governance issues raised by smart cities may require a rethinking of the existing law and policy infrastructure almost at pace with the emerging and evolving technologies.

The complexity of the governance challenges may be better understood when one considers the kind of data collected in smart cities. The narrower the categories of data, the more manageable data governance in the smart city will seem. However, the nature of information technologies, including the types and locations of sensors, and the fact that many smart cities are built incrementally, require a broad view of the types of data at play in smart cities. Here are some kinds of data collected and used in smart cities:

·traditional municipal government data (e.g. data about registrants or applicants for public housing or permits; data about water consumption, infrastructure, waste disposal, etc.)

·data sourced from private sector companies (e.g.: data about routes driven or cycled from companies such as Waze or Strava; social media data, etc.)

·data from individuals as sensors (e.g. data collected about the movements of individuals based on signals from their cell phones; data collected by citizen scientists; crowd-sourced data, etc.)

·data that is the product of analytics (e.g. predictive data, profiles, etc.)

Public sector access to information and protection of privacy legislation provides some sort of framework for transparency and privacy when it comes to public sector data, but clearly such legislation is not well adapted to the diversity of smart cities data. While some data will be clearly owned and controlled by the municipality, other data will not be. Further the increasingly complex relationship between public and private sectors around input data and data analytics means that there will be a growing number of conflicts between rights of access and transparency on the one hand, and the protection of confidential commercial information on the other.

Given that few ‘smart’ cities will be built from the ground up (with the potential for integrated data governance mechanisms), the complexity and diversity of smart cities data and technologies creates a stark challenge for developing appropriate data governance.

(Sorry to leave a cliff hanger – I have some forthcoming work on smart cities data governance which I hope will be published by the end of this year. Stay tuned!)